ai engineer

software engineer

senior software engineer

full stack engineer

lead software engineer

senior forward deployed engineer full stack

Databricks

<div>REQ ID: FEQ127R254
Location: Hybrid &ndash; London
As a Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data &amp; AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data.
This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.
The impact you will have:
<ul><li>Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration</li>
<li>Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer</li>
<li>Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.</li>
<li>Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.</li>
<li>Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.</li>
<li>Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.</li>
<li>Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.</li>
<li>Reusable Assets &amp; Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.</li>
</ul>What we look for:
<ul><li>Extensive experience in data engineering, data platforms &amp; analytics, or software engineering</li>
<li>Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks</li>
<li>Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one</li>
<li>Deep experience with distributed computing with Apache Spark&trade; and knowledge of Spark runtime internals</li>
<li>Familiarity with CI/CD for production deployments</li>
<li>Working knowledge of MLOps, ML/AI models and AI APIs</li>
<li>Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.</li>
<li>Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.</li>
<li>Documentation and white-boarding skills.</li>
<li>Experience working with enterprise clients and managing conflicts across a broad stakeholder range</li>
<li>Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.</li>
<li>Travel to customers 20% of the time</li>
<li>Databricks Certification preferred but not essential</li>
</ul><div>About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide &mdash; including Comcast, Cond&eacute; Nast, Grammarly, and over 50% of the Fortune 500 &mdash; rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark&trade;, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
 
 
Benefits
 
 
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. 
 
 
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.</div></div>

Senior Forward Deployed Engineer, Full Stack

<div>Requisition # CSQ327R148
As a Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data &amp; AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data.
This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.
The impact you will have:
<ul><li>Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration</li>
<li>Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer</li>
<li>Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.</li>
<li>Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.</li>
<li>Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.</li>
<li>Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.</li>
<li>Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.</li>
<li>Reusable Assets &amp; Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.</li>
</ul>What we look for:
<ul><li>Extensive experience in data engineering, data platforms &amp; analytics, or software engineering</li>
<li>Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks</li>
<li>Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one</li>
<li>Deep experience with distributed computing with Apache Spark&trade; and knowledge of Spark runtime internals</li>
<li>Familiarity with CI/CD for production deployments</li>
<li>Working knowledge of MLOps, ML/AI models and AI APIs</li>
<li>Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.</li>
<li>Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.</li>
<li>Documentation and white-boarding skills.</li>
<li>Experience working with enterprise clients and managing conflicts across a broad stakeholder range</li>
<li>Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.</li>
<li>Travel to customers 20% of the time</li>
<li>Databricks Certification</li>
</ul><div>About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide &mdash; including Comcast, Cond&eacute; Nast, Grammarly, and over 50% of the Fortune 500 &mdash; rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark&trade;, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
 
 
Benefits
 
 
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. 
 
 
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.</div></div>

Senior Forward Deployed Engineer - Full stack

<div><h2 class="jobSectionHeader">Description</h2>
<div>
We&rsquo;re looking for a highly skilled Forward Deployed AI Engineer to join our Health, Wealth &amp; Career (HWC) segment&mdash;where you&rsquo;ll design and deliver cutting-edge AI solutions that solve complex, real-world business challenges and shape the future of work.

This is a hands-on, high-impact role where you&rsquo;ll move beyond traditional development&mdash;partnering closely with stakeholders to translate ambiguous needs into scalable, AI-powered solutions that drive measurable value. You&rsquo;ll own the full lifecycle&mdash;from architecture and build through to deployment and adoption&mdash;embedding AI into real workflows, integrating enterprise systems, and ensuring solutions are secure, reliable, and truly user-centric. Sitting close to the business, you&rsquo;ll continuously refine solutions to maximise impact, efficiency, and adoption.

Why join us?
<ul>
<li>At WTW, you&rsquo;ll be part of our Health, Wealth &amp; Career (HWC) segment&mdash;where we use data, technology, and deep expertise to shape the future of work.</li>
<li>You&rsquo;ll collaborate across multiple lines of business&mdash;such as Retirement, Health &amp; Benefits, and Workforce Strategy&mdash;gaining exposure to diverse challenges and opportunities.</li>
<li>As the role evolves, you&rsquo;ll also help deliver innovative, AI-driven solutions directly to external clients, turning complex problems into scalable outcomes.</li>
<li>Together, we&rsquo;re creating more resilient, high-performing organizations&mdash;enhancing wellbeing, enabling better decisions, and driving sustainable business success at scale.</li>
<li>This is a hybrid role, with the flexibility of remote working alongside occasional time in the office to build strong relationships and collaborate effectively with stakeholders.</li> 
</ul>
The Role 
This position is ideal for an experienced Solutions Architect, Staff Engineer, or Technical Lead with a strong enterprise engineering background and a passion for applying it to AI-enabled systems. You&rsquo;ll bring deep expertise across modern full-stack technologies (.NET, Azure, SQL, React/Angular), along with experience in distributed systems, observability, and AI tooling such as LLMs, retrieval pipelines, and agentic workflows. 
Acting as a bridge between business and technology, you&rsquo;ll work across product, data science, architecture, and engineering teams&mdash;mentoring others, resolving production challenges, and scaling prototypes into robust, enterprise-grade solutions that deliver real impact.
<ul>
<li>AI solution delivery: Design and build AI-enabled applications, copilots, agents, extraction pipelines, prediction interfaces, and decision-support tools using foundation models, retrieval-augmented generation, structured outputs, and orchestration frameworks.</li>
<li>Forward deployed problem solving: Work directly with business teams, product owners, clients, or operational users to understand real workflows, constraints, data quality issues, and adoption barriers, then translate these into working technical solutions.</li>
<li>LLM and agent engineering: Build and tune LLM workflows, prompt strategies, schema-driven extraction, tool-calling patterns, agent orchestration, evaluation loops, and human-in-the-loop controls.</li>
<li>Enterprise integration: Integrate AI solutions with enterprise systems, APIs, data platforms, document repositories, workflow tools, observability platforms, and identity and access management services.</li>
<li>Production engineering: Ensure AI solutions meet enterprise standards for reliability, scalability, latency, maintainability, cost control, logging, monitoring, and operational support.</li>
<li>Evaluation and quality assurance: Create evaluation datasets, test harnesses, validation tools, regression checks, and quality review workflows to measure accuracy, extraction quality, hallucination risk, and business usefulness.</li>
<li>Architecture and technical leadership: Define solution architecture, engineering standards, reusable patterns, and implementation approaches for AI-enabled platforms and services.</li>
<li>Data and knowledge readiness: Work with engineering, data, and business teams to prepare structured and unstructured data, improve metadata, design retrieval strategies, and identify gaps in source content.</li>
<li>Security, privacy, and governance: Embed access controls, audit logging, data protection, responsible AI controls, security review, and compliance requirements into the AI delivery lifecycle.</li>
<li>Adoption and enablement: Support users through demos, pilots, training, feedback loops, documentation, and iterative improvement so that deployed AI solutions create measurable business value.</li>
</ul></div><h2 class="jobSectionHeader">Qualifications</h2>
<div>
What you'll bring
<ul>
<li>Significant professional experience in software engineering, technical leadership, solutions architecture, or platform engineering, ideally in enterprise-scale environments.</li>
<li>Proven ability to design and deliver production applications using modern engineering practices, including APIs, distributed systems, microservices, automated testing, CI/CD, observability, and cloud platforms.</li>
<li>Hands-on experience building AI-enabled systems, such as LLM pipelines, document extraction, structured output generation, AI-assisted analytics, prediction interfaces, or agentic workflows.</li>
<li>Experience working with business-critical systems where reliability, maintainability, operational support, and measurable business impact are essential.</li>
<li>Experience collaborating with data scientists, product managers, QA teams, architects, security teams, and senior stakeholders.</li>
<li>Track record of mentoring engineers, leading technical delivery, establishing engineering standards, and influencing teams beyond direct line management.</li>
</ul>
What we offer 
Enjoy a benefits package designed to help you thrive, both professionally and personally. You'll receive 25 days of annual leave plus an extra WTW day to relax and recharge. Our comprehensive health and wellbeing offering includes private healthcare, life insurance, group income protection, and regular health assessments, all giving you peace of mind. Secure your future with our defined contribution pension scheme, featuring matched contributions up to 10% from the company.

We support your growth and balance with hybrid working options, access to an employee assistance programme, and a fully paid volunteer day to make a difference in your community. On top of these, you can opt into a variety of additional perks including an electric vehicle car scheme, share scheme, cycle-to-work programme, dental and optical cover, critical illness protection, and much more. Start making the most of your career and wellbeing with a range of benefits tailored for you.

Equal Opportunity Employer 
We&rsquo;re committed to equal employment opportunity and provide application, interview and workplace adjustments and accommodations to all applicants. If you foresee any barriers, from the application process through to joining WTW, please email candidatehelpdesk@wtwco.com</div></div>

Forward Deployed AI Engineer

RS UK

Since 2015, RS has been committed to supporting some of the biggest names in video games such as World of Warcraft, Marvel Rivals, etc to global success in the fields of advertising and marketing. With a reach which spans up to 600 million gamers across China and beyond, today we expand user bases and market share by providing the following services:<ul><li>Ad strategy</li><li>Brand advertising</li><li>Performance-based advertising</li><li>Influencer marketing</li><li>Creative production</li><li>Live streaming</li><li>Overseas distribution</li></ul>We are hiring a founding Forward Deployed Engineer (FDE). You will be the founding member of our London-based Forward Deployed Engineering (FDE) team, building the internal systems, data infrastructure and AI-enabled workflows that power our gaming marketing operations. This role will work closely with strategy, media buying, client services, and creative teams to turn business needs into practical software solutions. The ideal candidate is both technically strong and commercially aware. You should understand how gaming marketing campaigns are run, how performance is measured, and how to design tools that help the team make faster, better decision.Key responsibilities:<ul><li>Design, build and maintain internal tools, dashboards, and automation that support marketing analysis and campaign operations</li><li>Integrate and process data from platforms, such as Reddit, Discord, TikTok, Meta, Google and other relevant sources</li><li>Develop monitoring and alerting systems that identify creative performance issues, audience sentiment shifts, and campaign risks early</li><li>Partner with media buying teams to build reporting frameworks and KPI logic for matrics e.g. CPI, CPM, CPC, CTR, and ROAs, and retention</li><li>Work with non-technical teams to understand business problems and convert them into clear technical requirements</li><li>Develop AI-assisted workflows for data interpretation, alerting, classification and reporting</li><li>Maintain documentation, improve internal processes, and ensure tools are reliable and scalable</li><li>Collaborate with stakeholders to test, refine, and roll out solutions across live campaigns</li><li>Feed operational insights back into product and engineering improvements</li></ul>Required skills and experience<ul><li>Strong expereince in software engineering, data engineering, full-stack development, or related technical roles</li><li>Proficiency in Python, SQL and API integration,and modern data tooling</li><li>Experience building internal tools, dashboards or workflow automation systems</li><li>Strong understanding of analytics, data pipelines and automation</li><li>Ability to communicate effectively across technical and non-technical teams</li><li>Comfortable working in a fast-paced environment with evolving priorities and ambiguous requirements</li><li>Strong problem-solving skills and attention to detail</li></ul>Preferred experience<ul><li>Experience in gaming, digital marketing, performance marketing, influencer marketing or creator ecosystems</li><li>Familiarity with social media or community platforms</li><li>Experience with AI tools, LLM workflows, or machine learning-assisted automation</li><li>Understanding of creative testing, media optimisation and campaign measurement methodologies</li><li>Experience building experimentation, monitoring, or decision-support systems</li></ul>Pay: From &pound;55,000.00 per yearWork Location: In person

Forward Deployed Engineer

Accenture

<div><h2 class="jobSectionHeader">Description</h2>
You build the systems that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent system in production, you have owned the eval harness, and you know what happens when your agent fails at 2am because you have lived it.
As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements.
This sits at the heart of the AI engineering talent market, demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability</li><li>
Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets</li><li>
Integrate and abstract across multiple LLM providers &mdash; OpenAI, Anthropic, Vertex AI, and open-source models &mdash; with fallback routing, token, cost, and latency management</li><li>
Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring</li><li>
Embed directly with client engineering teams to design, prototype, and deploy agentic solutions &mdash; workshops, proofs of concept, code-with sessions, and architecture walkthroughs</li><li>
Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster</li><li>
Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms</li></ul></div>
 
<div><h2 class="jobSectionHeader">Basic Qualifications</h2><ul><li>
5+ years of software engineering experience in production environments</li><li>
Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment &mdash; non-negotiable</li><li>
Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent &mdash; at production depth, not tutorial level</li><li>
Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs</li><li>
RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering</li><li>
LLMOps fundamentals: eval harness design, prompt versioning, and production observability</li><li>
Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)</li><li>
Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience</li><li>
Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure</li></ul></div>

AI Native SW Engineering Specialist

HCLTech

City Of London, England
 Job Summary
 
Job Title: Forward Deployed Engineer (FDE), Gemini Enterprise
 The FDE is a hybrid of a Staff Software Engineer and a Strategic Consultant. You will be the technical lead responsible for deploying Gemini Enterprise App and Gemini Enterprise Agent Platform within client environments. You will architect and code the "connective tissue" that allows Gemini agents to reason across private enterprise silos, execute long-running workflows, and adhere to strict corporate governance.
 
Key Responsibilities
 
Key Responsibilities
 <ul>
<li>Agentic Architecture: Design multi-agent systems using the Agent Development Kit (ADK), implementing patterns like hierarchical delegation and self-reflection.</li>
<li>Production Implementation: Move beyond prototypes. You will write the production code that integrates Gemini agents with legacy APIs, SQL/NoSQL databases, and ERP systems (SAP, Salesforce, etc.).</li>
<li>The "Grounding" Expert: Build and optimize RAG (Retrieval-Augmented Generation) pipelines using Vertex AI Search and BigQuery, ensuring agents have "zero-hallucination" access to enterprise truths.</li>
<li>Governance & Security: Deploy Agent Identity and Agent Gateway protocols to ensure every AI action is auditable, secure, and compliant with regional data residency laws.</li>
<li>Field-to-Product Loop: Act as the "eyes and ears" for Google’s core engineering. Identify common friction points in the Agent Platform and collaborate with product teams to build reusable "Skills" and modules.</li>
</ul>
Skill Requirements
 
Technical Requirements
 Domain Stack Expertise
 AI/ML Platform Gemini 3.0, Gemini Enterprise Agent Platform, Agent Studio, Vertex AI
 Engineering Python (Advanced), Go or Java, TypeScript, REST/gRPC APIs
 Data Architecture BigQuery, Vector Search, AlloyDB, Apache Beam / Dataflow
 Orchestration Agent Development Kit (ADK), LangGraph-native patterns, Kubernetes (GKE)
 Ops & Eval Agent Evaluation (Auto-SxS), Agent Observability, CI/CD for LLMs
 
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AI Solution Architect I

City Of London, England
 Job Summary
 
Job Title: Physical AI Engineer (Robotics & Agentic Systems)
 We are looking for an engineer to build the Physical AI solutions using Robotics and edge devices on Google stack. You will integrate Deepmind Robotics model with Gemini 3 foundation models to create autonomous agents that perceive, reason, and act in dynamic industrial environments. Your work will involve moving Physical AI from simulation (MuJoCo-Warp) to production-grade hardware at scale.
 
Key Responsibilities
 
Key Responsibilities
 <ul>
<li>Model Integration: Deploy Gemini Robotics-ER (Embodied Reasoning) models to enable robots to understand natural language instructions and physical causality.</li>
<li>Workflow Orchestration: Utilize the Gemini Enterprise Agent Platform to build agentic workflows that connect cloud-based reasoning with edge-based execution.</li>
<li>Simulation & Training: Use MuJoCo-Warp and G4 VMs (NVIDIA Blackwell) to run high-fidelity simulations, generating synthetic data to train robots on complex edge cases.</li>
<li>Hardware Abstraction: Work within Intrinsic Flowstate to develop hardware-agnostic "Skills" (robotic behaviors) that can be deployed across various robotic arms and sensors (Universal Robots, Foxconn, etc.).</li>
<li>System Optimization: Implement the JAX AI Stack (JAX, Flax, Optax) for efficient, accelerator-oriented computation on Google TPUs and NVIDIA GPUs.</li>
</ul>
Skill Requirements
 
Technical Requirements
 Category Stack Components
 Foundation Models Gemini 1.5/3.0, RT-2 (Robotics Transformer), Gemini Robotics-ER
 Software Platform Intrinsic Flowstate, ROS 2 (Robot Operating System), Python
 Compute & Infra Google Cloud Vertex AI, Google Distributed Cloud (Edge), TPUs
 Physics Engines MuJoCo-Warp, NVIDIA Isaac Sim integration
 Data & ML JAX, XLA (Accelerated Linear Algebra), Orbax (Checkpointing)
 
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Principal Engineer

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